Model Predictive Control System Design for Boiler Turbine Process

Abstract

<p>MPC is a computer based technique that requires the process model to anticipate the future outputs of that process. An optimal control action is taken by MPC based on this prediction. The MPC is so popular since its control performance has been reported to be best among other conventional techniques to control the multivariable dynamical plants with various inputs and outputs constraints. In the present work the control of boiler turbine process with three manipulated variables namely fuel flow valve position, steam control valve position and feed water flow valve position and three controlled variables namely drum pressure, output power and drum water level deviation [8] has been attempted using MPC technique. Boiler turbine process is very complex and nonlinear multivariable process. A linearized model obtained using Taylor series expansion around operating point has been used.</p>

An efficient application of particle swarm optimization in model predictive control of constrained two-tank system

“…This control concept is called the MPC [6]. Boiler turbine process control was performed with three manipulated variables and three controlled variables using MPC technique [7]. Optimal control sequence allows recalculation and feedback performance in MPC whenever a new measurement arrives; this is known as MPC.…”

LQG controller design for an industrial boiler turbine

“…In boiler turbines, the chemical and thermal energy is transformed to electricity. It is a highly complex, multivariable, time delayed and nonlinear process [3,4,5]. In a typical boiler turbine plant a header collects all the steam which is generated from number of boilers which is then distributed to several turbines through header.…”